Search results for " Computer-Assisted"
showing 10 items of 1033 documents
Combining split-and-merge and multi-seed region growing algorithms for uterine fibroid segmentation in MRgFUS treatments
2016
Uterine fibroids are benign tumors that can affect female patients during reproductive years. Magnetic resonance-guided focused ultrasound (MRgFUS) represents a noninvasive approach that uses thermal ablation principles to treat symptomatic fibroids. During traditional treatment planning, uterus, fibroids, and surrounding organs at risk must be manually marked on MR images by an operator. After treatment, an operator must segment, again manually, treated areas to evaluate the non-perfused volume (NPV) inside the fibroids. Both pre- and post-treatment procedures are time-consuming and operator-dependent. This paper presents a novel method, based on an advanced direct region detection model, …
Correlation between Topographic Parameters Obtained by Back Surface Topography Based on Structured Light and Radiographic Variables in the Assessment…
2017
<sec><title>Study Design</title><p>Optical cross-sectional study.</p></sec><sec><title>Purpose</title><p>To study the correlation between asymmetry of the back (measured by means of surface topography) and deformity of the spine (quantified by the Cobb angle).</p></sec><sec><title>Overview of Literature</title><p>The Cobb angle is considered the gold standard in diagnosis and follow-up of scoliosis but does not correctly characterize the three-dimensional deformity of scoliosis. Furthermore, the exposure to ionizing radiation may cause harmful effects particularly during the growth stage, includi…
Sub-threshold signal processing in arrays of non-identical nanostructures
2011
Weak input signals are routinely processed by molecular-scaled biological networks composed of non-identical units that operate correctly in a noisy environment. In order to show that artificial nanostructures can mimic this behavior, we explore theoretically noise-assisted signal processing in arrays of metallic nanoparticles functionalized with organic ligands that act as tunneling junctions connecting the nanoparticle to the external electrodes. The electronic transfer through the nanostructure is based on the Coulomb blockade and tunneling effects. Because of the fabrication uncertainties, these nanostructures are expected to show a high variability in their physical characteristics and…
An Extended Filament Based Lamellipodium Model Produces Various Moving Cell Shapes in the Presence of Chemotactic Signals
2015
The Filament Based Lamellipodium Model (FBLM) is a two-phase two-dimensional continuum model, describing the dynamcis of two interacting families of locally parallel actin filaments (C.Schmeiser and D.Oelz, How do cells move? Mathematical modeling of cytoskeleton dynamics and cell migration. Cell mechanics: from single scale-based models to multiscale modeling. Chapman and Hall, 2010). It contains accounts of the filaments' bending stiffness, of adhesion to the substrate, and of cross-links connecting the two families. An extension of the model is presented with contributions from nucleation of filaments by branching, from capping, from contraction by actin-myosin interaction, and from a pr…
Hadamard NMR imaging with slice selection
1996
Stochastic NMR imaging is one of the less common NMR imaging techniques. Nevertheless, stochastic rf excitation is characterized by some remarkable features: the rf excitation power is at least two orders of magnitude lower in comparison to conventionally pulsed NMR imaging schemes. Thus, the technique is of interest for imaging of large objects. The systematic noise inherent in images obtained with random noise excitation has been eliminated by using pseudorandom noise together with Hadamard transformation for data evaluation. Data acquisition times are comparable to those of ultrafast imaging techniques. For slice selection, z magnetization is destroyed outside the slice region with speci…
Digital Image Analysis Applied to Tumor Cell Proliferation, Aggressiveness, and Migration-Related Protein Synthesis in Neuroblastoma 3D Models
2020
Patient-derived cancer 3D models are a promising tool that will revolutionize personalized cancer therapy but that require previous knowledge of optimal cell growth conditions and the most advantageous parameters to evaluate biomimetic relevance and monitor therapy efficacy. This study aims to establish general guidelines on 3D model characterization phenomena, focusing on neuroblastoma. We generated gelatin-based scaffolds with different stiffness and performed SK-N-BE(2) and SH-SY5Y aggressive neuroblastoma cell cultures, also performing co-cultures with mouse stromal Schwann cell line (SW10). Model characterization by digital image analysis at different time points revealed that cell pro…
Classification of SD-OCT volumes with multi pyramids, LBP and HOG descriptors: application to DME detections.
2016
This paper deals with the automated detection of Diabetic Macular Edema (DME) on Optical Coherence Tomography (OCT) volumes. Our method considers a generic classification pipeline with preprocessing for noise removal and flattening of each B-Scan. Features such as Histogram of Oriented Gradients (HOG) and Local Binary Patterns (LBP) are extracted and combined to create a set of different feature vectors which are fed to a linear-Support Vector Machines (SVM) Classifier. Experimental results show a promising sensitivity/specificity of 0.75/0.87 on a challenging dataset.
Deep learning approach for prediction of impact peak appearance at ground reaction force signal of running activity
2020
Protruding impact peak is one of the features of vertical ground reaction force (GRF) that is related to injury risk while running. The present research is dedicated to predicting GRF impact peak appearance by setting a binary classification problem. Kinematic data, namely a number of raw signals in the sagittal plane, collected by the Vicon motion capture system (Oxford Metrics Group, UK) were employed as predictors. Therefore, the input data for the predictive model are presented as a multi-channel time series. Deep learning techniques, namely five convolutional neural network (CNN) models were applied to the binary classification analysis, based on a Multi-Layer Perceptron (MLP) classifi…
Ricci-flow based conformal mapping of the proximal femur to identify exercise loading effects.
2018
AbstractThe causal relationship between habitual loading and adaptive response in bone morphology is commonly explored by analysing the spatial distribution of mechanically relevant features. In this study, 3D distribution of features in the proximal femur of 91 female athletes (5 exercise loading groups representing habitual loading) is contrasted with 20 controls. A femur specific Ricci-flow based conformal mapping procedure was developed for establishing correspondence among the periosteal surfaces. The procedure leverages the invariance of the conformal mapping method to isometric shape differences to align surfaces in the 2D parametric domain, to produce dense correspondences across an…
On the use of the absorbed depth-dose measurements in the beam calibration of a surface electronic high-dose-rate brachytherapy unit, a Monte Carlo-b…
2019
PURPOSE To evaluate the use of the absorbed depth-dose as a surrogate of the half-value layer in the calibration of a high-dose-rate electronic brachytherapy (eBT) equipment. The effect of the manufacturing tolerances and the absorbed depth-dose measurement uncertainties in the calibration process are also addressed. METHODS The eBT system Esteya® (Elekta Brachytherapy, Veenendaal, The Netherlands) has been chosen as a proof-of-concept to illustrate the feasibility of the proposed method, using its 10 mm diameter applicator. Two calibration protocols recommended by the AAPM (TG-61) and the IAEA (TRS-398) for low-energy photon beams were evaluated. The required Monte Carlo (MC) simulations w…